Artificial Intelligence in Medicine: AI Research

• Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models

  World Health Organization, January 10, 2024.
• Principles for Augmented Intelligence Development, Deployment, and Use

  American Medical Association (AMA) Policy on AI, November 2023.
• Voluntary Commitments from Leading Healthcare Companies to Harness the Potential and Manage the Risks Posed by AI

  U.S. Department of Health and Human Services, December 14, 2023.
• CPT Appendix S: AI taxonomy for medical services & procedures

  American Medical Association (AMA), 2023.

   

  Source: PCOM Library

• AI Health Lab

  Led by Prof. Ying Ding from School of information, and Prof. Justin Rousseau from Dell Medical School at the University of Texas at Austin. AI Health Lab is made up of scholars and students from different fields and disciplines. They focus on cutting-edge research on AI in health and data-driven science of science.
• American College of Radiology (ACR) Data Science Institute

  Working with stakeholders to develop and implement radiology-related artificial intelligence applications. Host of the Informatics Learning Hub and "ACR Data Science Institute® AI Central database, the most complete and up-to-date online, searchable directory of commercially available Imaging AI products in the United States. Browse through more than 200 FDA-cleared products created by more than 100 manufacturers to find algorithms that best support your patients and workflows."
• Alliance for Artificial Intelligence in Healthcare

  The AAIH, consisting of technology developers, pharmaceutical companies, and research organizations, utilizes AI in healthcare to improve the quality of care.
• Cedars-Sinai

  Cedars-Sinai Medical Center's Department of Medicine houses the Artificial Intelligence in Medicine (AIM) research program. The AIM program aims to create software that can analyze three-dimensional images of the heart, like how a trained human operator would. The program measures critical parameters for understanding the state and behavior of the human heart using artificial intelligence techniques.
• Center on AI Research for Health

  At University of Southern "aims to nurture collaborations between researchers in AI and those in the health sciences." In 2023, they released projects on radiation oncology, neurodegenerative diseases and mental health.
• Gates Foundation

  Focused on the ethics of AI access and use, including the development of new technologies and their application in resource-poor settings. Research grants available. "The projects we selected focus on a wide array of critical health and development issues, including primary health care, education, agricultural development, women’s health, and nutrition. We are optimistic and excited about the diversity of problems being addressed because they often intersect."

   

  Source: PCOM Library

There is a multitude of databases and datasets in medicine related to AI and healthcare. These databases provide valuable resources for researchers and developers working on AI and machine learning applications in healthcare and medicine. They enable tasks such as imaging analysis, clinical decision support, predictive modeling, and drug discovery. Many are freely available for research. Always check the organization's policy on data re-use.

• Alzheimer’s Disease Neuroimaging Initiative

  The dataset for a longitudinal study includes neuroimaging, clinical, and genetic data from individuals with Alzheimer's disease, mild cognitive impairment, and healthy controls.
• Genomic Data Commons

  A dataset containing comprehensive cancer genomics, clinical data, and imaging data for various types of cancer enables research on the diagnosis, prognosis, and treatment of cancers.
• Medical Segmentation Decathlon

  This benchmark dataset features ten different segmentation tasks across various anatomical structures and imaging modalities, making it ideal for evaluating and comparing medical image segmentation algorithms.
• MIMIC-III

  A large, freely-available database of deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The database contains demographics, vital sign measurements taken at the bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (including post-hospital discharge).
• NIH Chest X-ray dataset

  A dataset comprising over 100,000 chest X-ray images released by the National Institutes of Health (NIH), annotated for the presence of common thoracic pathologies.

   

  Source: PCOM Library